The internet and media enabled portable computing devices have dramatically altered the processes for generating and consuming media content. Presently, users can consume media content virtually anywhere at any time, as long as they have access to a media capable device with an internet connection. The convenience of being able to view media content via the internet, essentially on demand, has resulted in explosive growth of internet media consumption. Internet media traffic is currently approaching a majority of consumer internet traffic, and the rate of demand is projected to continue increasing.
The sheer quantity of media content available to users can make selecting content for consumption challenging. Millions of people around the world have the capability to produce media content, and popular online services can receive tens of hours worth of newly uploaded user-generated content every minute. In addition, traditional media outlets now have the ability to enable consumers to access archives containing large amounts of older media content, along with newly generated content. Users may overlook available content well suited to their individual preferences because of an inability to locate or identify the content.
A technique that been commonly employed to assist users in identifying media content for consumption includes recommending media content that shares attributes with other media content. Additionally, content is often organized into categories based on one or more attributes. However, due to the large quantity of media content available, recommending and/or organizing content based on attributes may provide limited information regarding desirability of the media content to the user. Additionally, due to the large quantities of media content available, reviewing and refining recommendations based on attributes can be a tedious and time consuming process.